README

Replication codes for Holzer, J. & McConnell, K., "The Ambiguity of Fishing for Fun". 

1. Note

This study uses proprietary data. Researchers seeking access to the data may contact NOAA Fisheries' Office of Science and Technology (https://www.fisheries.noaa.gov/about/office-science-and-technology).

2. Files

The study consists of two parts: the estimation of the models and the simulations. 
The main part estimates anglers' preferences. The simulation calibrates the fishery for each of the coastal states and years and generates one-year predictions. 

A. Estimation:

 - data_prep.do: code for cleaning and formatting the survey raw data
 - mlogit_model.do: estimates the linear (mlogit) utility model (Table A-7).
 - models.m: estimates the alpha-maxmin, CARA, and Linear (clogit) utility models (Tables 1, A-5, A-6). 

models.m uses the following user-written functions:

 - likelihoodLinear.m: evaluates the log-likelihood function corresponding to the linear utility model
 - likelihoodGrad_cara.m: evaluates the log-likelihood function and its gradient for the CARA utility model
 - likelihoodGrad_ambiguity.m: evaluates the log-likelihood function and its gradient for the alpha-maxmin utility model

B. Simulations

The simulations use data on catch-per-trip and catch-at-length at the species and year level, for directed trips that targeted or caught summer flounder. These data come from a data request to MRIP and need to be requested from MRIP by interested researchers. 
The main files for the simulations are:

 - calibratedSeasonStateYEAR.m: calibrates the number of choice occasions for each of the four utility models so that the number of expected trips for that state and year (e.g. New Jersey in 2019) matches the observed data. 
 - predictedSeasonStateYEAR.m: predicts the number of trips and landings for each of the four utility models for that state and year (e.g. New Jersey in 2020).

Each of the nine coastal states in Table 2 is calibrated for each of the years in 2009-2019 and then used to generate one-year predictions. We provide the example files for New Jersey for the period 2019-2020., but the rest of the files are available from the authors upon request. These files use the preferences' estimates from the estimation stage, and demographic information of survey respondents from the cleaned data generated by data_prep.do. 
Additionally, these simulation files use the following datasets as inputs: 

 - CatchPerTripYEAR.mat: generated by generate_distributions_catch_per_trip.m. This code uses the user-written function CatchTripDistribution.m, and the function gendist.m (available for download at: https://www.mathworks.com/matlabcentral/fileexchange/34101-random-numbers-from-a-discrete-distribution).
 - ProbFlukeSizesYEAR.txt, ProbScipSizesYear.txt and ProbBSBSizesYEAR.txt, which were generated from the data coming from the data request to MRIP by the code PreparingCatchDistributionsSpeciesYEAR.do
 - trip_costs_NE.xlsx: from a data request to the Northeast Fisheries Science Center and is generated from the raw data of the latest expenditure survey (report available at: https://spo.nmfs.noaa.gov/sites/default/files/TM201.pdf). These data need to be requested from the Office of Science and Technology by interested researchers.
 - mrip_directed_sf_trips_2009_2020.xlsx: obtained directly from MRIP Query Tool (https://www.fisheries.noaa.gov/data-tools/recreational-fisheries-statistics-queries).
 - mrip_SUMMER_FLOUNDER_catch_series: obtained directly from MRIP Query Tool (https://www.fisheries.noaa.gov/data-tools/recreational-fisheries-statistics-queries).
 - AvgeCatchTrip.xlsx: auxiliar file that includes the average catch per trip per species at the state and yearly level, generated from the data from MRIP.

The calibration and prediction files for each state and year also use the user-written pstar.m, which evaluates the difference between the actual and the expected keep for a given minimum size limit.
The analysis of welfare in Table 5 uses the file predictedSeasonNJ2020.m, with the calibrated number of choice occasions for each model that year, by changing the bag and size limits according to each of the scenarios specified in Table 5.
Lastly, the main results are generated by the files:

 - MSEComputations.m: which generates Figure 1 and the data for Tables 3, 4 and A-8. This file uses the user-written function TestFSD.m that implements Barret-Donald Test and comes from "Econometric Analysis of Stochastic Dominance" by Y-J. Whang (2019).
 - violin_plots.do: generates the violin plots in the online appendix (Figures A-4 through A-7).
The data used in the calibration exercise of section 3 comes from MRIP Query Tool (mrip_directed_sf_trips_2009_2020.xlsx) combined with information on summer flounder bag and size limits in each state and year (from the Mid-Atlantic Fishery Management Council Summer Flounder Fishery Information Reports for each year, available at https://www.mafmc.org/): 
 
- calibrationExample.xls



